Financially adaptive clinical trials via option pricing analysis
通过期权定价分析设计财务自适应临床试验AI 解读 ↓
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通过期权定价分析设计财务自适应临床试验
- 研究问题
- 如何量化临床试验随新信息提前终止的财务价值，并设计使资助方经济价值最大化的停止决策边界？
- 方法与思路
- 作者将试验信息积累建模为一系列实物期权，据此设计提前停止边界，并在选定疾病领域分析自适应融资的表现。
- 材料陈述的贡献
- 摘要称无效疗法情形下，所考察成本指标最多可下降百分之四十六；有效疗法情形下可降低资本成本并提高估值。
- 阅读关注点
- 应核对疗效信息过程、市场收益与成本假设、停止边界求解，以及最高降幅对应的场景和融资安排的评价基准。
- 阅读边界
- 仅据所给 RePEc 出版社摘要，最高降幅不能视为普遍或平均效果；未说明临床统计约束及经济价值结论的完整假设。
原文摘要
The regulatory approval process for new therapies involves costly clinical trials that can span multiple years. When valuing a candidate therapy from a financial perspective, industry sponsors may terminate a program early if clinical evidence suggests market prospects are not as favorable as originally forecasted. Intuition suggests that clinical trials that can be modified as new data are observed, i.e., adaptive trials, are more valuable than trials without this flexibility. To quantify this value, we propose modeling the accrual of information in a clinical trial as a sequence of real options, allowing us to systematically design early-stopping decision boundaries that maximize the economic value to the sponsor. In an empirical analysis of selected disease areas, we find that when a therapy is ineffective, our adaptive financing method can decrease the expected cost incurred by the sponsor in terms of total expenditures, number of patients, and trial length by up to 46%. Moreover, by amortizing the large fixed costs associated with a clinical trial over time, financing these projects becomes less risky, resulting in lower costs of capital and larger valuations when the therapy is effective.